Internal Sensor Based Kinematic Parameters Estimation using Acceleration/Deceleration Motion

Kaiki Fukutoku, Hirotoshi Masuda, T. Murakami
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引用次数: 0

Abstract

Motion measurement systems play an important role in a wide range of fields such as robot motion control and human motion analysis. Motion measurement methods using a camera, which is an external sensor, have problems such as low sampling rate and limited measurement range. On the other hand, the method using the encoder or inertial sensor, which is an internal sensor, has almost no limitation on the measurement range. Moreover, it can be measured at a high sampling rate. However, when using the internal sensor, it was necessary to use the kinematic model and kinematic parameters of robots and humans. Errors in these parameters lead to reduced accuracy in kinematic calculations. Therefore, the control performance and analysis accuracy are reduced. To solve these problems, we propose a method for estimating kinematic parameters using the inertial sensor. The proposed method uses a kinematic relational expression in the acceleration dimension. Therefore, kinematic parameters can be estimated without using absolute position information. In this paper, the proposed method is applied to the 3-link manipulator and the human body. The effectiveness of the proposed method is evaluated by comparing the estimated link length with the measured value.
基于内部传感器的加减速运动参数估计
运动测量系统在机器人运动控制和人体运动分析等广泛领域发挥着重要作用。摄像机作为一种外部传感器,其运动测量方法存在采样率低、测量范围有限等问题。另一方面,使用编码器或惯性传感器的方法,这是一种内部传感器,几乎没有测量范围的限制。此外,它可以在高采样率下测量。然而,在使用内部传感器时,必须使用机器人和人的运动学模型和运动学参数。这些参数的误差导致运动学计算精度的降低。因此,降低了控制性能和分析精度。为了解决这些问题,我们提出了一种利用惯性传感器估计运动参数的方法。该方法在加速度维度上使用运动关系表达式。因此,无需使用绝对位置信息即可估计出运动学参数。本文将该方法应用于三连杆机械臂和人体。通过将估计的链路长度与实测值进行比较,评价了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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